The aims of this competitive 5 year renewal application are to use magnetic resonance (MR) imaging: (1) to delineate brain abnormalities in schizophrenia (SZ); (2) to determine whether brain abnormalities are related to cognitive and clinical symptom clusters; (3) to determine whether any, all, or only some of these abnormalities are static and/or progressive; (4) to determine whether shape deformations are better discriminators than volume measures; (5) to determine whether while matter tracts show a different orientation and asymmetry; and, (6) to determine to what extent automated brain measures can replace manual measures. To accomplish these goals we will evaluate MRI frontal, temporal, parietal, basal ganglia, thalamus, CSP, PT, cerebellum, fornix, corpus callosum, and sulco-gyral pattern abnormalities in chronic SZ (n=50;1/2 more positive symptoms and 1/2 more negative symptoms), fist episode psychotic patients (n=60 SZs; n=60 bipolar), and controls (n=50 for chronics; n=75 for first episodes). We will conduct repeat MR scans at 1.5 and 3 years to determine which brain regions, in which patient groups, progress over time. Based on research over the previous grant period, we hypothesize that SZ with more positive symptoms and formal thought disorder will demonstrate MR left- lateralized temporal lobe volume reductions, and cognitive impairments characterized by selective deficits in verbal processes, memory, and associations. In contrast, we hypothesize that SZs with more negative/deficits symptoms will demonstrate that bilateral and frontal lobe volume reductions that will progress over time, and more cognitive impairments, particularly attention and working memory. We further predict that patients with a greater number and severity of neurodevelopmental abnormalities (e.g., CSP, PT, sulco-gyral pattern) will show a negative symptom pattern (see above). We further predict that first episodes of SZs will show the greatest volume reductions over the 1.3 and 3 year period, and that patients with a more negative symptom profile at illness onset will show more progressive changes than first episode patients with a more positive symptom profile. We will also evaluate shape, in addition to volume, to determine the specificity of shape deformations to SZ, and to determine whether they best characterize patients with primarily positive versus primarily negative symptoms. Further, we will use brain tensor maps to trace white matter tracts, where we predict that patients with negative symptoms will show bilateral differences while tensor maps to trace white matter tracts, where we predict that patients with negative symptoms will show left- lateralized differences. Finally, we will use warping techniques and model based segmentation of shape to determine to what extent we can replace manual RO1 measures with automated RO1 measures. Using these techniques for imaging the brain we hope to understand better the pathophysiology of SZ.